Identification of pseudogenes in the Drosophila
melanogaster genome
Paul M. Harrison*, Duncan Milburn, Zhaolei Zhang, Paul Bertone &
Mark Gerstein
Dept. of Molecular Biophysics & Biochemistry,
Yale University,
266 Whitney Ave.,
P.O. Box 208114,
New Haven, CT 06520-8114,
U.S.A.
*corresponding author
Phone: (203) 432 5065
Fax:
(509) 691 6906
Email: harrison@csb.yale.edu
(submitted to Nucleic Acids Research, September 16th 2002)
(revised version submitted, November 15th 2002)
Abstract
Pseudogenes are copies of genes that cannot produce a protein. They can be detected from
disruptions to their apparent coding sequence, caused by frameshifts and premature stop codons.
They are classed as either processed pseudogenes (made by reverse transcription from an mRNA)
or duplicated pseudogenes, arising from duplication in the genomic DNA and subsequent
disablement.
Historically, there is anecdotal evidence that the fruit fly (Drosophila
melanogaster) has few pseudogenes. Investigators have linked this to a high deletion rate of
genomic DNA, for which there is evidence from genetic experiments on genome size. Here, we
apply a homology-based pipeline that was previously developed to identify pseudogenes in other
eukaryotic genomes, to the fruit fly, so as to derive the first complete survey of its pseudogene
population. We find approximately 100 pseudogenes, with at least a sixth of these as candidate
processed pseudogenes. This gives a much lower proportion of pseudogenes (compared to the
size of the proteome) than in the genomes of other eukaryotes for which data are available
(human, nematode and budding yeast). Closest matching proteins to Drosophila pseudogenes are
significantly longer than the average protein in its proteome (up to ~60% more than the average
protein’s length), in contrast to the situation in the three other eukaryotic genomes. This may be
due to the persistence of fragments of longer genes. In the fly pseudogene population, we found
most pseudogenes for serine proteases (which are more abundant in the Drosophila lineage
compared to the other eukaryotes), immunoglobulin-motif-containing proteins and cytochromes
P450.
Data on the sequences and positions of the putative pseudogenes are available at:
http://www.pseudogene.org/fly.
The detection of a small number of pseudogenes in the
Drosophila genome and the higher mean length for the closest matching proteins to pseudogenes
(possibly because remnants of genes encoding longer proteins are more likely to persist) are
further evidence for a high deletion rate of genomic DNA in the fruit fly. This data is useful for
molecular evolution study in Drosophila.
Keywords: fruit fly, bioinformatics, molecular evolution, DNA loss, annotation
_______________________________________________________________
Introduction
Pseudogenes are copies of genes that do not produce a full-length functional
protein chain. Their apparent protein-coding sequences are disrupted by frameshifts and
premature stop codons as evolution progresses
1,2,3.
They occur in two forms: firstly,
duplicated pseudogenes arise from duplications of a gene (or an exon), that become
disabled and subsequently are degraded; secondly, processed pseudogenes arise from
reverse transcription of a messenger RNA and reintegration of the resultant cDNA into
genomic DNA
1,2,3.
The latter type of pseudogene can arise as a by-product of LINE-1
retrotransposition in humans
4.
Surveys have recently been performed on the
pseudogene populations of budding yeast, nematode and chromosomes 21 and 22 for
human, with a further analysis of over 2000 ribosomal-protein pseudogenes in the whole
human genome
5,6,7,8.
The procedures derived in these papers have been applied to the
Drosophila genome in the present study to derive an initial overview of the pseudogene
population of this fly. Here, we report the detection of about 100 putative pseudogenes in
the Drosophila genome, and present analysis of some of their characteristics, such as the
length of their matching proteins and their most common functional groupings.
Results and Discussion
Numbers and distribution of pseudogenes
We found 110 pseudogenes in the Drosophila genome, which is about 1 for every
~130 proteins encoded in the genome. This proportion is much lower than in the other
eukaryotic genomes for which studies on pseudogene populations have been completed
(Table 1). For example, in the single-celled budding yeast (S. cerevisiae) there are over
220 pseudogenic ORFs, which is about 1 for every ~30 encoded proteins
5.
In human,
our surveys have shown that there may be one duplicated and one processed pseudogene
for every four genes 7. A recent paper detailing comparative analysis of the genomes of
Anopheles gambiae and Drosophila melanogaster describes detection of 176
pseudogenes in Drosophila by searching for disabled protein homology; however, our
methods our more conservative, as we disregard any disabled homology fragments that
look like disabled extensions to known genes (such as might arise in the last exon of a
gene) (see Methods)
transposable elements
9;
also, we disregard any pseudogenic copies of proteins from
10.
On a related note, we recently found that the fly has more
decayed remnants of genes than other sequenced eukaryotes that are undetectable by
standard gene prediction and sequence alignment procedures
11.
Processed pseudogenes do not have introns (as they are derived from messenger
RNA transcripts), and, if recently integrated into the genome, have detectable
characteristic features such as a polyadenine tail with an upstream polyadenylation signal
3,7.
We examined the fly pseudogenes for evidence of being processed (Table 1). About
one-sixth (19/110) of the Drosophila pseudogenes have no obvious introns and both a
polyadenylation signal and a downstream polyadenine-rich stretch in the genomic DNA,
and up to a third of the pseudogenes (34/110) have some evidence of processing (see
Methods and Table 1 for details). There are six pseudogenic copies of single-exon genes
that could be either processed or duplicated pseudogenes. The only previously welldocumented evidence of processing in Drosophila is an alcohol dehydrogenase
retrosequence, which is part of the gene jing-wei in many Drosophila species (but not
melanogaster)
pseudogene
12,
13,14.
and was originally identified as an anomalously conserved processed
Our data show that processed pseudogenes are comparatively rare in
the fruit fly genome (Table 1), indicating either a low rate of generation, or a high rate of
deletion from the genome. Indeed, our procedures could be over-assigning pseudogenes
as processed, particularly in situations where the pseudogene fragment is too small to
discern the original intron-exon boundaries, so the figure of 34/110 pseudogenes as
processed should be considered an upper bound.
The pseudogene population and its subpopulation of candidate processed
pseudogenes appear to be dispersed randomly along the chromosomes (Figure 1) (as for
genes, there are no notable large-scale gradients or clusterings in their positioning
15,
although we must emphasize that we only have a small population). However, there
appears to be clustering of pseudogenes within 2Mb of either side of the 16Mb of
pericentromeric heterochromatin on chromosome 2 (see 2L and 2R in Figure 1). Such
large blocks of heterochromatin are also seen around the X- and 3rd-chromosome
centromeres.
These clusterings comprise sixteen pseudogenes, of which eight were
judged to be candidate processed pseudogenes (two of these are homologous to parts of
the protein Osa
16
); of the others, two are homologous to a retroviral reverse transcriptase
(InterPro motif IPR000477
17).
This pericentromeric area may be a ‘cold-spot’ for
genomic DNA deletion.
Length of closest matching proteins to pseudogenes
We calculated the mean length of the closest matching proteins for pseudogenes
of the genomes of budding yeast, nematode worm and human (chromosomes 21 and 22
only). We compared this with the same data for the Drosophila genome pseudogenes
(Table 1). In Drosophila, coding sequences that give rise to pseudogenes tend to be
rather longer than the average coding sequence, in contrast to the situation in other
organisms. Specifically, we found that closest-matching proteins for pseudogenes tend to
be ~60% longer than the average Drosophila protein (Table 1). (Their mean length
reduces to ~20% longer than average when seven outlying matching proteins of >3000
residues are deleted (Table 1 footnote).) This length observation may arise because
remnants of longer genes can persist for longer in the genomic DNA than shorter genes,
and withstand very high deletion rates of genomic DNA in Drosophila
18.
There is evidence from experiments investigating genome size that Drosophila
has a very high genomic DNA deletion rate
18,19.
This has traditionally been thought to
be the reason that few Drosophila pseudogenes have been discovered in the past
20.
There is some evidence that the underlying deletion rate of genomic DNA is also high in
nematodes
21,22;
however some gene families, particularly types of G-protein-coupled
receptors, appear to acquire and ‘use up’ more novel duplications, resulting in a lowered
net rate of deletion of pseudogenes in the nematode genome. There is also a marginally
significant difference in the same comparison for the budding yeast pseudogene data
(Table 1 footnote); however, in this case, the proteins that are closest matches to
pseudogenes tend to be somewhat shorter than the average protein encoded by the
genome. This finding may be related to the high concentration of pseudogenes and
homologs of pseudogenes near the telomeres of the budding yeast genome 5.
Most common families and functions
InterPro motifs
17
and GO function categories
23
were mapped onto the fruit fly
pseudogenes via annotations for their closest matching protein sequences. The topranking motifs and functions are listed in Table 2.
The most common InterPro motifs are for serine proteases (there are multiple GO
function
category designations
for
these
enzymes
as
well,
as
‘serine-type
endopeptidase’), and immunoglobulin-like domain motifs. The serine proteases are types
of proteins that are very abundant in the fly, but are very rare in the nematode worm (C.
elegans), budding yeast (S. cerevisiae) and the weed A. thaliana, and of intermediate
abundance in the human proteome (see InterPro website: http://www.ebi.ac.uk/interpro).
The S1 class of proteases (Table 2) is thought to have roles in digestion, the complement
cascade and in various signalling pathways in the fly
15.
This finding continues the
theme of pseudogenes tending to occur for lineage-specific or lineage-expanded classes
of proteins, observed previously for other eukaryotes
1.
Interestingly, there are also
multiple pseudogenes for the cytochromes P450 (Table 2(b)), which are proteins that
have a ‘broad’ substrate specificity. In other organisms, classes of proteins that have a
‘breadth’ of substrate specificity, or ‘binding diversity’, have many pseudogenes, such as
the chemoreceptors in the nematode 6, and the immunoglobulins and olfactory receptors
in human
7,24.
The fact that the cytochromes P450 were not ‘counted’ in the InterPro
motif listings demonstrates the utility of combining different methods (here both GO
function categories and InterPro motifs) to characterize the functional role of sequences.
Notably, we find only one G-protein-coupled receptor (GPCR) pseudogene,
which contrasts to the situation in the nematode worm and in the human genome, where
several hundred such pseudogenes are found
6,24.
This may be because of a fundamental
difference in the organization of GPCR genes in the fly; they are distributed among many
loci in small clusters of one, two or three genes
15,
whereas in the nematode and in
human, there are large arrays of dozens of genes with interspersed pseudogenes
6,24.
Also, we detect no ribosomal-protein pseudogenes; in contrast, processed pseudogenes
from transcripts for these proteins are abundant and ubiquitous in the human genome,
suggesting that appropriate reverse transcriptase specificity is not as available or as potent
in the fly
7,8.
There are two assignments of candidate processed pseudogenes each for
serine proteases and for immunoglobulin-like domains; removing them from the counts
does not change the identity of the ten most common domains (Table 2).
Conclusions
We have completed an initial survey of the pseudogene
population in the Drosophila genome. We find about 100 pseudogenes, with at least onesixth of these as candidate processed pseudogenes. Two features of the fly pseudogene
population arguably arise from a comparatively high genomic DNA deletion rate in the
fly, relative to the rate of duplication of genes and gene parts: (i) there is comparatively
small number of putative pseudogenes (Table 1), relative to the genomes of other
eukaryotes; (ii) closest matching proteins to pseudogenes appear to be rather longer than
the average protein sequence in the proteome. Finally, the most pseudogenes occur for
serine proteases (which are relatively abundant in the Drosophila lineage, compared to
the other eukaryotes), immunoglobulin motif—containing proteins and cytochromes P450.
Data relating to this paper are available at http://www.pseudogene.org, including
chromosomal positions and protein sequences with disablements. We have re-mapped
our annotations onto Release 3 of the genome, and are currently honing our methods for
pseudogene detection in Drosophila with consideration of underlying substitution rates in
the DNA, and other concepts. Our fruit fly data further add to the picture of evolution of
the size and diversity of eukaryotic proteomes. In the human genome, there seems to be a
clear correlation between the numbers of processed pseudogenes and the amount of non-
coding DNA on a chromosome (reference 8; Zhang, Z., unpublished data). However, as
can be seen in Table 1 (and references
1,7,25),
no obvious relationship has yet emerged
between the size of a pseudogene population, the size of a proteome, and the amount of
coding and non-coding DNA in genomes as whole entities. Detailed analysis of many
more genomes will further help in deconvoluting the forces that shape these populations
of sequences.
Methods
Searching for putative pseudogenes in D. melanogaster
We applied procedures for detection of pseudogenes based on the identification of
protein homology in the genomic DNA that is disabled by frameshifts or premature stop
codons; these procedures have been described in detail previously 7. As for our study of
human chromosomes 21 and 22, we ensured that we minimized the number of disabled
extensions like those observed for known genes (see Methods of ref.
7
for the complete
procedure; an extension length minimum of 24 residues was found to be suitable). We
used Releases 1 and 2 of the Drosophila genome and the accompanying annotations
15.
We disregarded any sequences that may have arisen from disabled copies of transposable
elements
10.
As before, we assigned as candidate processed pseudogenes, any sequences
that (i) are of substantial length (>70% of the length of the closest matching protein
sequence) and that have no obvious introns, or (ii) have evidence of polyadenylation and
no obvious introns 7. Evidence of polyadenylation is defined as a discernible canonical
AATAAA polyadenylation signal followed within 50 nucleotides by a region of elevated
polyadenine content (>30 adenines in a 50 nucleotide stretch), within 1000 nucleotides
from the end of the detected homology 7. Drosophila transcripts have a greater tendency
than transcripts of the other eukaryotes to use the canonical AATAAA polyadenylation
signal
26.
We have re-mapped the pseudogene annotations onto the recent Release 3 of
the fly genome.
Comparison with existing pseudogene annotation
In addition, we examined existing annotations for fly pseudogenes downloaded
from the FLYBASE website (http://www.flybase.org). We found 10 previously reported
pseudogenes that are in euchromatic DNA, that are not obviously associated with a
transposable element and whose sequences were available. However, once we set aside
those that do not occur in the sequenced fly strain or that are truncations (and would not
be detected by our procedures), we are left with only 3 existing annotations (two
cytochrome P450 pseudogenes and one esterase pseudogene
15,27),
each of which are
recovered in our study.
Assignment of features in pseudogenes
InterPro motif families
17
were assigned to pseudogenes by transferring
annotations from the closest matching Drosophila protein.
Lists of matches for
Drosophila proteins were downloaded from the InterPro proteome analysis website
(http://www.ebi.ac.uk/proteome). Similarly, Gene Ontology (GO) annotations for
function (downloaded from http://www.geneontology.org) were also transferred
23.
Figure Legend
Figure 1: Distribution of putative pseudogenes in the fly genome. The position along
each chromosome of each candidate processed pseudogene is indicated by a purple spot.
Positions of other pseudogenes are indicated by blue spots. The y-axis is the position in
megabases along the chromosome or chromosome arm, with the chromosomes or
chromosome arms arrayed along the x-axis.
Tables
Table 1: Numbers and mean lengths for proteins and pseudogenes in
four eukaryotes
Organism
Number of Number
proteins
of Number
pseudogenes b
of Mean length Mean
processed
of protein d
pseudogenes
Human a
Nematode worm
Budding yeast
Fruit fly
927
for pseudogenes
189
317 (+43)
342
20732
1100 (18.9)
104
435 (+15)
450
6340
221 (28.7)
0
467 (+29)
424 *
14332
110 (130.3)
34 c
500 (+50)
808 **
a
This data is for chromosomes 21 and 22 only
b
The proportion of proteins to pseudogenes is given in brackets.
.
c This value is for pseudogenes (i) that are of substantial length (>70% the length of the
closest matching organismal protein) and have no introns (where a matching protein does
have introns) or (ii) that have some evidence of polyadenylation. See Methods for more
detail. These procedures are described in 7.
d
Standard deviation of the sample mean is given in brackets.
* The difference between mean lengths of yeast proteins in general and those that are
closest matches to pseudogenes is marginally significant (p<0.06) using normal statistics.
** The difference between mean lengths of fruit fly proteins in general and those that are
closest matches to pseudogenes is very significant (p<0.0001) using normal statistics.
Removing the outlying matchers of seven fragments whose lengths exceed 3000 amino
acids, reduces the mean to 610 residues (p<0.02).
of
matching protein
384 (2.4)
7
length
Table 2: Prevalent InterPro motif families and Gene Ontology (GO)
categories for the fruit fly pseudogenes
(a) InterPro motifs a
Number
of Number of Description of InterPro motif family
pseudogenes
proteins
with motif
with motif
7 [2]
187 (4)
chymotrypsin serine protease, family S1 (IPR001314)
7 [2]
206 (3)
Serine protease, trypsin family (IPR001254)
6 [2]
132 (10)
Immunoglobulin / major histocompatibility complex (IPR003006)
5 [2]
100 (14)
Immunoglobulin C-2 type (IPR003598)
5 [0]
162 (7)
Proline-rich extensin (IPR002965)
5 [0]
80 (28)
Chitin-binding peritrophin A (IPR002557)
5 [0]
347 (1)
C2H2-type Zinc finger (IPR000822)
4 [0]
44 (53)
Protein of unknown function DUF227 (IPR004119)
4 [0]
88 (20)
EGF-like domain (IPR000561)
(b) GO function-ontology categories b
Number
of
Description of GO category
pseudogenes
with
GO
category
4
cytochrome P450
(GO:0015034, function)
3
serine type endopeptidase (GO:0004252, function)
2
myosin ATPase (GO:0008570, function)
2
RAN protein binding (GO:0008536, function)
2
structural constituent of larval cuticle (GO:0008010, function)
2
DNA binding (GO:0003677, function) (from homology to the gene Osa
16
)
a
The numbers of pseudogene sequences that have each type of domain (regardless of
how many domains are detected in each sequence) are listed in decreasing order. Only
the top ten counts are listed. In square brackets are the counts for candidate processed
pseudogenes. In round brackets in the second column are the rankings for the count of
genes with motifs in the whole proteome.
b
The counts of GO function categories for the pseudogene sequences in decreasing
order of occurrence; only those function categories with multiple occurrences are listed.
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